docs: def load_tag(corpus, path):
          """
          Iterate over all speakers on load them.
          Collect all utterance-idx and create a subset of them.
          """
          tag_idx = os.path.basename(path)
          data_path = os.path.join(path, 'by_book')
          tag_utt_ids = []
  
          for gender_path in MailabsReader.get_folders(data_path):
              # IN MIX FOLDERS THERE ARE NO SPEAKERS
              # HANDLE EVERY UTT AS DIFFERENT ISSUER
              if os.path.basename(gender_path) == 'mix':
                  utt_ids = MailabsReader.load_books_of_speaker(corpus,
                                                                gender_path,
                                                                None)
  
                  tag_utt_ids.extend(utt_ids)
  
              else:
                  for speaker_path in MailabsReader.get_folders(gender_path):
                      speaker = MailabsReader.load_speaker(corpus, speaker_path)
                      utt_ids = MailabsReader.load_books_of_speaker(corpus,
                                                                    speaker_path,
                                                                    speaker)
  
                      tag_utt_ids.extend(utt_ids)
  
          filter = subset.MatchingUtteranceIdxFilter(
              utterance_idxs=set(tag_utt_ids)
          )
          subview = subset.Subview(corpus, filter_criteria=[filter])
          corpus.import_subview(tag_idx, subview)